Safety Stock

Executive Summary

Dynamic safety stock in ERP and external supply planning systems is commonly desired to be activated by companies.

Extensive testing and many observations illustrate that the standard dynamic safety stock calculation is incorrect.

In this article, we cover a wide number of topics around dynamic safety stock.

Introduction to Dynamic Safety Stock

This article covers the topic of dynamic or enhanced safety stock (SS) in SAP. This is one of the most common requested SS areas to be active in SAP SNP by SAP customers. However, the issues brought up in this article regarding the dynamic SS calculation also apply to the formula generally and as used in other supply planning applications. You will learn about the issues with dynamic safety stock have come from experiences on SAP projects.

The Concept of Dynamic Safety Stock

The standard dynamic safety stock formula was developed to provide a variable quantity of stock to account for the variability in demand and supply. Dynamic SS is often presented as something that companies want to move to as it is more sophisticated than other methods of setting SS.

Most companies people that use the following dynamic safety stock formula.

I have colorized the lead time-oriented values as orange, and the demand values as blue. “Z” is the service level. Roughly speaking the formula accounts for variability on both the supply side and the demand side, while increasing or decreasing the safety stock in conjunction with the service level.

The Dynamic Safety Stock Settings in SAP APO

Both SAP ECC and SAP APO (SNP) have the dynamic safety stock calculation. In fact, the dynamic safety stock calculation is the only area of functionality in ERP systems to account for variability and to account for service level. As we will discuss, and provide the specific reasons, the dynamic safety stock is rarely implemented in ERP systems. This means that the vast majority of companies that use ERP have no way of accounting for service levels in ERP.

Therefore, while companies almost universally declare their interest in high service levels, there is no real way to making the ERP system follow service levels in an automated fashion.

This is a functionality which allows the SS to vary depending upon supply and demand variability. These values are entered into the Lot Size tab of the Product Location Master, as can be seen in the screenshot below.

Dynamic safety stock is set on the Lot Size tab of the Product Location Master in SAP APO.

This allows the safety stock to be set at the product location combination.

Extended/Dynamic Safety Stock

I have often wondered why no client that I have worked with has ever configured this functionality. I had often attributed it to the problem in maintaining this master data. It should be understood that this is the standard dynamic SS method that is taught in textbooks. That is, it is in no way SAP intellectual property. SAP is simply using what is the inventory management textbooks.

Interestingly, one person I discussed this topic with who had tested it, they stated that the SS it came up with was high (this is, of course, relative, as it calculates the correct SS.) However, another comment was that it was not very adjustable, and that adjustability was a requirement for them. In fact, planners fall into a habit of adjusting the SS when it should be auto adjusted. This same feedback was repeated through various discussions at around six different clients throughout the years.

More specifically, I question if the requirement will lead to good planning outcomes.

Dynamic SS and the First Release and How Commonly Dynamic Safety Stock is Used

I was once with a client that was interested in implementing dynamic SS in their first release. My view is that the first release is best for dialing in the most basic functionality. Most implementations put too much functionality into their first release.

I have seen dynamic SS get yanked out of a number of implementations, or I have heard of it getting disabled after initial use. My view is that very few companies are presently using dynamic SS in APO.

Therefore, it is a “high risk” functionality, which is better left to later releases of implementation. Essentially, I see dynamic SS to be a high-risk luxury with a very low probability of successful implementation. In my view, there are many more important areas of functionality to work on, and simpler methods of SS such as days’ coverage are more durable and much higher probability of success.

Interesting Comment from LinkedIn on Why Dynamic SS Often Fails

I found this comment from David Ginsberg on a LinkedIn discussion which I found interesting.

“Most statistical models on inventory fail to work operationally because they focus exclusively on “deviation of demand”. There are two additional criteria that must be taken into account… replenishment lot size and supplier lead time. If I could have “any” quantity “tomorrow”; that would require a different safety stock model then “some” in “six months.””

While SAP’s dynamic SS functionality does have a location for deviation of demand, in fact, it is rarely used even with companies that have attempted dynamic SS. Therefore, David Ginsberg’s criticism would apply to how SAP dynamic SS is implemented, also if it does not use to the ability of the functionality.

“A third limitation of the safety stock model is that it carries the additional inventory throughout the inventory cycle. Why carry safety stock when your replenishment order has just arrived and your inventories are far above safety thresholds? Often it is better to bring in the next replenishment order a period or two early. This is referred to as “safety lead time” and offers superior operational and financial model to safety stock. Planning the number of stock out periods to manage and then reducing the lead time to cover them will buy you more operational and financial performance than tweaking the math of demand-based statistical models.”

I also found this final quote from David Ginsberg interesting.

“If there were good tools for this, they would be used in the stock market, not planning parts. Avoid the “we predict the future better than anyone” pitches.”

How Not to Calculate Safety Stock

One of the primary mistakes made when setting SS is setting it reactively and not controlling its setting. For instance, safety stock is often used as a form of forecast adjustments by supply planning. If the forecast is considered too high, SS might be reduced, and vice versa.

Different individuals can have input to SS, but ultimately SS should be controlled by a policy and centrally by a supply chain planning group. While this is often the case regarding having some central responsibility at some companies, there is still more often than not control is given to make the changes given to a small group.

Having groups such as sales or individuals in distributed locations adjust the SS — under the argument that they “know the products” means that there is an increasing likelihood that the safety stock will be changed by people that don’t understand how SS fits with other supply planning parameters.

As is explained further in this article calculation of the overall inventory available for SS and cycle stock. And then assigned to the inventory on a relative basis.

This is a weakness of many of the inventory parameters when they calculate SS individually by the system. All inventory parameters should be calculated based upon the relative consumption of whatever the resource limitations are.

George Plossl on Safety Stock

George Plossl has an interesting observation as to how safety stocks are often set that conforms with my experience at numerous clients.

“Guestimates: Guestimates are probably the most frequently used, being easiest to apply, and are based on planners’ frequent personal judgement. They usually increase immediately after a shortage occurs but are rarely decreased.

Rules of Thumb: These are equally irrational, and require additional work to apply. A popular one bases SS on A-B-C inventory classification; expensive A-items should have little, moderate B-items some more, and low-cost C-items plenty. This ignores the protection furnished by lot sizes in excess of immediate requirements; C-items usually have very large order quantities and short replenishment lead times; they may not even need safety stock. Conversely, A-items are exposed more frequently to stock outs because of frequent reordering.”

Evaluating the Dynamic Safety Stock Formula

The dynamic safety stock formula is often discussed, but it is rarely evaluated. When we look at just the formula, it is difficult to see why this should give the right answer on safety stock.

Also, I was not able to find the original paper where this formula was first published. This means that the many papers on dynamic safety stock are not pointing back to the original publication.

Let us look at the formula in segments.

The Dynamic Safety Stock Formula Segments

The Service Level Portion of the Formula

The Forecast Error and Lead Time Portion of the Formula

Error Measurements as an Absolute Value

1. The Service Level Portion of the Formula

The first part of the formula makes sense. That is when using the inverse of the normal distribution as applied to the service level.

This is for product location combinations with a reasonable volume. For low volume demand, a different probability distribution would be applied as the arrival of demand for low volume demand is not normally distributed. This provides the “ratcheting” effect consistent with increases or decreases in service level.

It is well known that a different probability distribution is to be used for lower volume items than higher volume items. Some vendors have proposed measuring the probability distribution of each item and applying the probability distribution that fits.

2. The Problems with Lead Time Portion of the Formula

The following questions naturally came to me when reviewing the formula:

Why is the average lead time multiplied by the standard deviation of demand?

Why would squaring the value this lead to the right output?

3. The Problem with Standard Deviation of Demand History

Why is only the standard deviation of the demand used instead of the forecast error?

If the variance of the demand history is accounted for by the forecast than the safety stock would calculate as lower. One can have a seasonal forecast that is high in variability but is accounted for by the forecast (that is it has a low error). However, using the standard dynamic safety stock formula, this would calculate a high safety stock.

The dynamic safety stock formula produces strange results. Normally the dynamic safety stock is not tested before it is activated in SAP. That is companies assume the dynamic safety stock formula will work properly.

Strange Behavior of the Dynamic Safety Stock Formula

The standard dynamic SS formula seems to have some strange assumptions, it also produces strange output. How many people know this? Not many. Many people propose using dynamic safety stock without testing the formula.

But if the formula is tested, it does not produce the expected safety stock that I would expect from changes in variability. This gets to the topic of the evidence for dynamic SS working in companies, either at SAP customers or other.

Dynamic safety stock calculations (there are several) are standard in inventory textbooks. The calculation is standard in supply planning applications. There is not any real evidence that the dynamic safety stock is useful when applied to industry. My hypothesis for this is that while the principle is correct, the standard dynamic safety stock formula itself is flawed.

The Lack of Evidence for the Effective Use of Dynamic Safety Stock Formula

It would be less necessary to intensively analyze the logic of the standard dynamic SS formula if there was a large amount of evidence that the standard dynamic SS formula was being widely used in companies.

But there isn’t evidence of this that I could find.

The mere fact that a formula is published doesnot prove it is in use and does not prove it is useful.

In fact, the evidence is quite to the contrary, that the dynamic SS formula is rarely used. And it is not for lack of trying. Every one of my previous clients that have tested enabling the dynamic safety stock calculation eventually turned it off.

Practical Versus Theoretical Questioning of the Formula

At first, I thought this might have been because of the high forecast inaccuracy causes companies not to want to carry the calculated safety stock. My detailed evaluation of the standard dynamic safety stock formula calls the standard formula into question. This is not just questioning practically (i.e. is it implemented successfully), but theoretically as well.

Creating a Customized and Constrained Safety Stock

A customized and safety stock calculator which takes into account variability, as well as constraints, can be developed per client. It must be customized for the limitations of the specific client.

The following are some extra areas to look out for when developing a safety stock calculation which incorporates forecast error.

Zero Periods of Demand

The Proper Forecast Error Measurement in the Time Dimension

1. Zero Periods of Demand

The standard dynamic SS formula does not use a forecast error, but instead a standard deviation of demand. However, when you create a custom dynamic SS formula, one can use forecast error. This has advantages in that forecast error is far more often discussed within forecasting departments and companies generally regarding the forecast than the standard deviation of demand.

Conclusion

While many people attempted to list the standard SS formulas, I think what needs to be discussed is why the dynamic SS calculation is not used in companies. Rather than spending more time on reiterating complex SS formulas, the question needs to be asked:

Why?

Part of the answer lays with the high forecast error that most companies have. However, a second problem is the dynamic SS formula itself.

Contrary to what one might think, I found that there have not been studies that show that the dynamic SS formula works well for companies. In testing of the formula myself, I was not impressed with the output. This lead me to develop my SS formula, which is explained in this article.

Finally, while the standard dynamic SS formula will not meet a company’s inventory needs, the other end of the spectrum of guessing or not using math to determine safety stock is also not effective. In fact, even the most common approach of setting a safety days of supply combined with a lower value (to protect the SS when demand declines) leaves out many other dimensions that improve the SS.

The Problem: Maintaining Inventory Parameters

A major part of replenishment is inventory parameters. These parameters include values like safety stock or days of supply, rounding value, reorder point, lot size/economic order quantity and minimum order quantity. Whatever the planning procedure that is used, these parameters control what the supply planning system does.

Testing of the extracted parameters of ERP and external supply planning systems clearly shows that these values are poorly maintained. The result is far worse planning results than could be obtained otherwise.

Being Part of the Solution: Our Evolution of Thinking on Maintaining Reorder Points in ECC or APO

Maintaining reorder points in APO or ECC comes with a number of negatives that tend to not be discussed. One issue is that when using APO or ECC, the reorder points are typically managed on a “one by one” basis. This leads to individual planners entering values without any consideration for how inventory parameters are set across the supply network. We have developed a SaaS application that sets the inventory parameters for ECC or APO or both systems externally, and that allows for simulations to be created very quickly. These parameters can then be easily exported and it allows for far more control over the parameters in APO and ECC. Both APO and ECC are designed to receive parameters, they are not designed to develop the parameters.

In our testing, the approach, which is within the Brightwork Explorer is one of the most effective methods for managing planning in SAP applications.

Financial Disclosure

Financial Bias Disclosure

Neither this article nor any other article on the Brightwork website is paid for by a software vendor, including Oracle, SAP or their competitors. As part of our commitment to publishing independent, unbiased research; no paid media placements, commissions or incentives of any nature are allowed.

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This presentation illustrates the problems with SAP support and how Brightwork SAP Support addresses these shortcomings.

What Kind of Support is This?

If this does not sound like standard support, you are right. And that is the point.

We designed our support to help our customers get the most out of SAP, not to maximize our margin or to try to protect previous sales inaccuracies. We know how to get your SAP applications working better.

To see the broader information about our SAP support see our main SAP Support Page.

References

Safety Stock and Service Level Book

Important Features About Safety Stock

Safety stock is one of the most commonly discussed topics in supply chain management. Every MRP application and every advanced planning application on the market has either a field for safety stock or can calculate safety stock. However, companies continue to struggle with the right level to set it. Service levels are strongly related to safety stock. However, companies also struggle with how to set service levels.

How Systems Set Safety Stock

The vast majority of systems allow the setting of safety stock by multiple means (static, dynamic, adjustable with the forecast in days’ supply, etc..). However, most systems do not allow the safety stock to be set in a way that is considerate of the inventory that is available to be applied.By reading this book you will:

Understand the concepts and formula used for safety stock and service level setting.

Common ways of setting safety stock.

Service levels and inventory optimization applications.

The best real ways of setting both service levels and safety stock.

Chapters

Chapter 1: Introduction
Chapter 2: Safety Stock and Service Levels from a Conceptual Perspective
Chapter 3: The Common Ways of Setting Safety Stock
Chapter 4: The Common Issues with Safety Stock
Chapter 5: Common Issues with Service Level Setting
Chapter 6: Service Level Agreement
Chapter 7: Safety Stock and Service Levels in Inventory Optimization and Multi-Echelon Software
Chapter 8: A Simpler Approach to Comprehensively Setting Safety Stock and Service Levels

Introduction

This document is designed to provide an explanation of why the Inventory Steering Committee has asked for an enhancement, which would add the Safety Days’ of Supply to the Safety Stock Case Quantity to arrive at a total safety stock.

Safety stock in days supply and safety stock in cases (entered into the product location master) needs to have the ability to work as an “and” statement instead of only an “or” statement. The enhancement request is based on business requirements for the inventory steering committee. The A and B SKUs that have full-service volume use safety stock in days and cases and needs to maintain cases of safety stock with a target of days’ supply on top. This is the direction of the RSP organization regarding inventory policy.

Safety Stock Setting at One Client

At one client most of the products are coded SZ, which means they only show the safety stock from the product location master. This was done because SM, which uses the higher of Safety Days’ Supply, ceased functioning months ago. However, once SM works, the safety stock will be the max of the safety stock and the Safety Days’ Supply from the location product master (which adjusts per the forecast), some product locations can be setup to use the SM method. This SM method is shown in the graphic below:

When the enhancement is complete, the projected safety stock will look like this, for product locations that are coded to use this enhanced method.

However, one question would naturally arise, which is listed below:

The Reasons for the Enhancement Request

This enhancement is desired primarily a way of taking care of some of the issues with full-service products. The idea is to keep A & B products at safety time.

Confusion on Safety Stock Currently

According to the Steering Committee, it can be confusing as to what the numbers mean when SNP performs a comparison that is the “or” between safety stock as entered in the product location master and Safety Days’ Supply. The issue is that the full-service requirement is a fixed service requirement. The requirement for the safety stock calculation is to have a high level of safety stock or a “base,” and then to have the Safety Days’ of Supply added to this base. However, sometimes promotions change the forecast upward.
Track Record of Effectiveness: Full-service products, the use of a safety stock approach, which adds the safety stock in cases to the Safety Days’ Supply, has proven effective in R/3. Its previous effectiveness in practice in R/3 has naturally led to this enhancement request to make this safety stock method available within APO/SNP as well.

Comfort Level

All the safety stock calculations in R/3 are comfortable to the business. Unfortunately, the approach with full-service products has had to be changed to account for the different way SNP manages safety stock.

Loss in Functionality of Safety Stock as of 7.0

One issue driving this request is that the functionality, which allowed the system to take the safety stock in cases or the Safety Days’ Supply, is not presently working.

The Use of the Requested Enhancement Safety Stock Method

The enhancement request is not to replace all product locations that have the SM method (higher of the two) with the additive solution, but instead to create the additive solution functionality so that it is an additional option that we can choose in the material master for those products where it is applicable. For other material location combinations, the current SM solution is relevant.

Conclusion

The request for additive safety stock for the safety stock value case quantity entered into the product location master and the safety stock in Days’ Supply is from the Inventory Steering Committee and is based upon using R/3 safety stock functionality that has proven to work very well for full-service products.

Advice on Enjoying the Multimedia Presentation

To see the full screen just select the lower right-hand corner and expand. Trust us, expanding makes the experience a whole lot more fun.

This presentation illustrates the problems with SAP support and how Brightwork SAP Support addresses these shortcomings.

What Kind of Support is This?

If this does not sound like standard support, you are right. And that is the point.

We designed our support to help our customers get the most out of SAP, not to maximize our margin or to try to protect previous sales inaccuracies. We know how to get your SAP applications working better.

To see the broader information about our SAP support see our main SAP Support Page.

References

I cover safety stock in the following book.

Safety Stock and Service Level Book

Important Features About Safety Stock

Safety stock is one of the most commonly discussed topics in supply chain management. Every MRP application and every advanced planning application on the market has either a field for safety stock or can calculate safety stock. However, companies continue to struggle with the right level to set it. Service levels are strongly related to safety stock. However, companies also struggle with how to set service levels.

How Systems Set Safety Stock

The vast majority of systems allow the setting of safety stock by multiple means (static, dynamic, adjustable with the forecast in days’ supply, etc..). However, most systems do not allow the safety stock to be set in a way that is considerate of the inventory that is available to be applied.By reading this book you will:

Understand the concepts and formula used for safety stock and service level setting.

Common ways of setting safety stock.

Service levels and inventory optimization applications.

The best real ways of setting both service levels and safety stock.

Chapters

Chapter 1: Introduction
Chapter 2: Safety Stock and Service Levels from a Conceptual Perspective
Chapter 3: The Common Ways of Setting Safety Stock
Chapter 4: The Common Issues with Safety Stock
Chapter 5: Common Issues with Service Level Setting
Chapter 6: Service Level Agreement
Chapter 7: Safety Stock and Service Levels in Inventory Optimization and Multi-Echelon Software
Chapter 8: A Simpler Approach to Comprehensively Setting Safety Stock and Service Levels

Software Ratings: Supply Planning

Software Ratings

Brightwork Research & Analysis offers the following free supply planning software analysis and ratings. See by clicking the image below:

Executive Summary

Introduction to Safety Stock in SAP

In this article, we will cover the safety stock method in SAP. The safety stock method controls how the safety stock is derived.

Using SAP SNP Versus SAP ERP for the Safety Stock Calculation?

One of the selling points of SNP over SAP ERP is that has more ways to derive safety stock from multiple values. For instance, the Safety Stock Method SM has SNP look to either the higher of the value that is entered into the Location Product Master or the calculated Days’ Supply. This is based upon the number of days entered into the Safety Stock in the Material Master. This flows to the Location Product Master is a stable value. The Days’ Supply value changes the actual safety stock depending upon the requirements.

This is one of the advantages of safety stock in SAP SNP versus SAP ERP. SAP ERP allows you to combine the “hard-coded” safety stock or the Days’ Supply (which does not make much sense incidentally). However, allowing the system to take the higher of the two values allows the safety stock to flex up during times of high demand usually, but then not flex too far down when demand decreases. Many companies become comfortable with how this is handled in SAP ERP.

Imagine Their Surprise

Then, they are often perplexed when the functionality concerning safety stock goes down between SAP SNP and SAP ERP. These settings in SAP ERP will flow over to the Location Product Master. The settings are unusual concerning the safety stock because the Safety Stock Method is entirely dependent upon which values are populated in ERP. This is described in this article.

The SM Safety Stock Method and the SNP Optimizer

Unfortunately, and I was not able to find this problem documented on the internet or SAP’s SDN site, the optimizer does not recognize safety stock if SM is used in SNP.

This is another thing I had to learn from a project, and while I have not established if it is related to SCM 7.0 versus 5.1, it may be a new problem in SCM 7.0.

SAP has no pro-active mechanism for communicating all the things that are broken in the system. They tend to wait for the client to find issues, and then tell them that it’s broken and that they are working on it. Other SAP consultants seem to do their best to hide the broken components from the client. Remember, to most SAP consultants; the “customer” is either SAP or the consulting company they work for — the paying client is on the bottom of the totem pole.

Conclusion and Next Steps?

The SM Safety Stock Method does not work with the optimizer. This means that currently, companies that use the optimizer must understand that they must use either the Safety Stock that is hard-coded into the Material Master or the Safety time/act.cov, but the system will not use either of the two. The way to approach this is to set only the Safety Stock quantity or the Days of Supply. If only the Safety Stock quantity is entered into the Material Master then the Safety Stock Method will change to SB, while if only the Days of Supply is used then the Safety Stock Method in APO becomes SZ. This would mean using the mass maintenance transaction to change every Location Product combination in ERP to hold only a Safety Stock Quantity or a Days Supply.

However, there is more to this than simply the master data change. When analyzing this for one project, it was brought up that the current Safety Stock Quantities had been set up on the low side because they were designed really only to protect the lower end of the range, and primarily the Safety Stock Quantities were developed to work with the Days of Supply, or intended to work with the SM Safety Stock Method.

Once Days of Supply is taken out of the equation for certain Location Products, that the Safety Stock Quantity would have to be increased. This, of course, requires that the business go through and increase these Safety Stock Quantities to the appropriate levels if the Days of Supply is never used.

Advice on Enjoying the Multimedia Presentation

To see the full screen just select the lower right-hand corner and expand. Trust us, expanding makes the experience a whole lot more fun.

This presentation illustrates the problems with SAP support and how Brightwork SAP Support addresses these shortcomings.

What Kind of Support is This?

If this does not sound like standard support, you are right. And that is the point.

We designed our support to help our customers get the most out of SAP, not to maximize our margin or to try to protect previous sales inaccuracies. We know how to get your SAP applications working better.

To see the broader information about our SAP support see our main SAP Support Page.

References

Service Level & Safety Stock Setting

Service Level & Safety Stock Setting

Setting service levels and inventory can be performed far more easily than is done at the vast majority of companies. Click the image to see how.

Executive Summary

We cover the Lot Size Tab, the PP/DS Tab, the Demand Tab, the SNP 1 Tab, the SNP 2 Tab, and the Procurement Tab.

Introduction to the Product Location Master

You will learn from this article how one of the most important master data elements in APO works to control APO.

What is the Product Location Master?

The product location master stores parameters that apply to a combination of the product and the location.

The focus of this article is on the Product Location Master is on the following tabs that relate to SNP and PP/DS.

Lot Size

PP/DS

Demand

SNP 1

SNP 2

Procurement

The Lot Size Tab

There is a lot to go over here, so we will just focus on a few of the settings. First, you can choose Lot for Lot (the exact shortage amount is ordered), Fixed Lot Size or by Period (a preset amount is used). Next to this field allows you to enter the lot size. By period groups together lots from different periods. If you select by the period you can choose from the following:

You can also choose Reorder Point. If you chose the Reorder Point, you have the following options.

As you can see each of these selections has further qualifications that you can add.

In the lower portion of the tab you can hard code safety stock, reorder point, max stock level, service level, demand forecast error. Some of these form the inputs to creating a safety stock, others allow a full hard coding of safety stock.

The PP/DS Tab

The first options are the planning procedure. Defines for each planning relevant event that can occur for a location product, which action is executed by Production Planning and Detailed Scheduling (PP/DS) in SAP APO if this event occurs.

The planning package is an optional selection. In the case of a planning package for a supersession chain, this corresponds to the condition that the products in a supersession chain always have to be planned together in procurement planning.

The next selection is the planning Heuristic or PP/DS Heuristic which is to be used. There are many many heuristics to chose from, each with their specific benefits. We will discuss these benefits in a separate post on PPDS heuristics.

The planning group is simply a grouping of the product. It is also optional. However, a planning group can serve as an aggregation device. The planning group is also available for the propagation range as a selection criterion.

The lower portion of the tab is concerned with horizons. Essentially how far out the product should be planned? These horizons affect different modules such that a single product, can have different horizons for different planning purposes. Most of these are values that you enter rather than selections. The exception being the SNP horizon.

Demand Tab

Requirements Strategies are set up in the IMG. See this article for details.

The first sub-tab has to do with Dependent Requirements. If you select “Always coll requirements,” the system creates dependent and stock transfer requirements for the product in the make-to-stock segment.

And then whether the consumption should be forward or backward. Backward consumption simply means that sales orders, dependent requirements or material reservations consume forecasted demand that lies within the consumption period and before the requirements date. Forward consumption does not allow this.

The consumptive group is in conjunction with descriptive characteristics to enable the forecast to be consumed by sales orders and related orders, at a more detailed level than the location product.

Now we go to the pegging sub tab. The most critical setting is the Fixed Pegging option.

This determines whether the product has fixed pegging and thus whether the pegging from a production planning run is permanent.

The next selection supposed to be set if you want to use dynamic pegging, that is the capacity and inventory is available for pegging during every MRP run. The right side has to do with variances and are not used all that frequently. Below and towards the right, you can set if you want to use total receipts.

If you set this indicator, the system assigns a receipt element to just one requirement element for the product during dynamic pegging. (The requirement element must thus completely consume the receipt element.)

Use total stock. If you set this indicator, the system may assign a receipt element to just one requirement element for the product during dynamic pegging. (The requirement element must thus completely consume the receipt element.) The final sub-tab shows the stock types which should be considered available. That is you set which of the types of stock you want taken into account.

SNP 1 Tab

“Gives the penalty cost rate per day that is used by the SNP Optimizer to weight the delayed delivery of a product with regard to the planned delivery date. The penalty for delayed delivery of the requirement quantities is measured per base unit of quantity.)” – SAP Help

Conclusion

Basically, these tabs are very powerful in controlling SNP and PPDS. Some controls, such as safety stock have levers in both the Product Master as well as within the heuristic (if the right heuristic is selected). Some of these settings will be CIFed over from ECC, but no all of them. Therefore, after the CIF is complete, it’s important to go through the product master with your client and make sure your settings are doing what you want them to in terms of output to the plan.

Advice on Enjoying the Multimedia Presentation

To see the full screen just select the lower right-hand corner and expand. Trust us, expanding makes the experience a whole lot more fun.

This presentation illustrates the problems with SAP support and how Brightwork SAP Support addresses these shortcomings.

What Kind of Support is This?

If this does not sound like standard support, you are right. And that is the point.

We designed our support to help our customers get the most out of SAP, not to maximize our margin or to try to protect previous sales inaccuracies. We know how to get your SAP applications working better.

To see the broader information about our SAP support see our main SAP Support Page.

References

Constrained Book

How Constrained Supply and Production Planning Works

Constraint-based planning generates something that is appealing to all manufacturers: a feasible supply and production plan. However, constraint-based planning software was first implemented over twenty years ago, and yet few companies (as a percentage that all that have tried) have mastered constraint-based planning.

Getting the Real Story

This book provides the background information, detailed explanations, step-by-step examples, and real-life scenarios to assist a company in becoming proficient at constraint-based planning, along with valuable information about what SAP APO can do for supply and production planning in reality, rather than just in theory. Here you will learn about resources the mechanism for constraining the plan in APO and for determining the feasibility of the plan and how constrained supply and production planning work together (and how they don’t).

Also, this book talks about constraint-based planning at the supplier level: can a vendor’s production be capacity-constrained?

By reading this book, you will learn:

The different resources available in APO, how production resources differ from supply planning resources, and the role resources and other significant constraints play in constraint-based planning.

How constraints integrate across the supply planning and production planning applications.

The areas of disconnect between supply and production planning applications, and between SNP and PP/DS in particular.

The difference between unconstrained (or infinite) planning and constraint-based planning.

The benefits of constraint-based planning and how it differs from capacity leveling.

Various types of demand, and how backward and forwards were scheduling work.

The benefits of using production constraints in the supply planning system, and how SNP and PP/DS can be synchronized to produce the desired output.

The methods that can do constraint-based planning in SNP and PP/DS–heuristics, CTM, and optimization–and how to configure these methods.

The difference between hard and soft constraints, and how to plan using multiple constraints.

Chapters

Chapter 1: Introduction

Chapter 2: Understanding the Basics of Constraints in Supply and

Production Planning Software

Chapter 3: Integrating Supply and Production Software with Constraints

Chapter 4: Constraint-based Methods in APO

Chapter 5: Resources

Chapter 6: Capacity-constraining Vendors/Suppliers

Chapter 7: The Disconnection Points Between Supply Planning and Production Planning